I am specifying a SEM model with TYPE is COMPLEX. I have 47 clusters but 57 estimated parameters. the model estimation terminated normally, but I always got a warning. The warning says the problem involving parameter 47. then i changed orders of factors, and i found it's still parameter 47's problem even though it's become a different parameter. I next tried to constrin more parameters so that there are less number of parameters than clusters, and in this way the warning dissapeared. But this is not what I wanted with the model. Is there a way to fix this problem without having to sacrifice the model specification? Thanks!! The full warning is as below

THE STANDARD ERRORS OF THE MODEL PARAMETER ESTIMATES MAY NOT BE TRUSTWORTHY FOR SOME PARAMETERS DUE TO A NON-POSITIVE DEFINITE FIRST-ORDER DERIVATIVE PRODUCT MATRIX. THIS MAY BE DUE TO THE STARTING VALUES BUT MAY ALSO BE AN INDICATION OF MODEL NONIDENTIFICATION. THE CONDITION NUMBER IS -0.208D-16. PROBLEM INVOLVING PARAMETER 47. THIS IS MOST LIKELY DUE TO HAVING MORE PARAMETERS THAN THE NUMBER OF CLUSTERS.

It is advisable to have more clusters than parameters. It is not known how serious the consequences of this are. Only a Monte Carlo study could say for sure. There is no way around this other than to make your model more parsimonious.